Zeno runs, where infinitely many actions occur within finite time, may arise in Timed Automata models. Zeno runs are not feasible in reality and must be pruned during system verification. Thus it is necessary to check whether a run is Zeno or not so as to avoid presenting Zeno runs as counterexamples during model checking. Existing approaches on non-Zenoness checking include either introducing an additional clock in the Timed Automata models or additional accepting states in the zone graphs. In addition, there are approaches proposed for alternative timed modeling languages, which could be generalized to Timed Automata. In this work, we investigate the problem of non-Zenoness checking in the context of model checking LTL properties, not only evaluating and comparing existing approaches but also proposing a new method. To have a systematic evaluation, we develop a software toolkit to support multiple non-Zenoness checking algorithms. The experimental results show the effectiveness of our newly proposed algorithm, and demonstrate the strengths and weaknesses of different approaches.

Testing provides a probabilistic assurance of system correctness. In general, testing relies on the assumptions that the system under test is deterministic so that test cases can be sampled. However, a challenge arises when a system under test behaves non-deterministiclly in a dynamic operating environment because it will be unknown how to sample test cases.

Non-functional requirements (NFRs) are often regarded as the key success factor in building high quality software. However, most of the requirements elicitation methods are centered on discovering functional requirements only. This paper presents a novel NFRs elicitation approach aiming at empowering requirements analysts with a knowledge repository that aids to the process of capturing precise NFRs during elicitation interviews. The knowledge repository is composed of two layers: the upper layer of feature models and the lower layer of the QoS ontology. The case study of the stock trading domain illustrates the relationships and cooperations of the two layers.

Web service composition is a low cost and efficient way to leverage the existing resource and implementation. In current Web service composition implementations, the issue of how to define the role for a new composite Web service has been little addressed. Adjusting the access control policy for a new composite Web service always causes substantial administration overhead from the security administrator. Furthermore, the distributed nature of Web service based applications makes traditional role mining methods obsolete. In this paper, we analyze the minimal role mining problem for Web service composition, and prove that this problem is NP-complete. We propose a sub-optimal greedy algorithm based on the analysis of necessary role mapping for interoperation across multiple domains. Simulation shows the effectiveness of our algorithm, and compared to the existing methods, our algorithm has significant performance advantages. We also demonstrate the practical application of our method in a real agent based Web service system. The results show that our method could find the minimal role mapping efficiently.

Little is known about how to preprocess the noise in legacy access control data when migrating to the Role-based Access Control model. This paper presents an experience report on the noise preprocess method of the legacy access control data of several financial systems. The main goal of this project is to improve the quality of the roles obtained via role mining.